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Taxonomy: IM- Particle (e.g., Proton) CT: Quality control
| MO-E115-GePD-F8-2 | Comparison of Patient Fluoroscopic Water-Equivalent Thicknesses to a Common Patient-Equivalent Phantom G Fong*, K Wunderle , Cleveland Clinic Foundation, Cleveland, OH |
| MO-E115-GePD-F8-4 | Development of An Automated Digital Radiography QC Program A Zhao1*, A Sampson1, (1)University of Texas Health Science Center at San Antonio ,San Antonio, TX |
| MO-I345-GePD-F9-6 | Predicting Patient Mis-Centering in CT as a Methodology for Monitoring CT Technologist Performance C Burton*, Harvard University, Boston, MA |
| PO-GePV-P-4 | Computed Tomography Dose Monitoring Systems, Technical Issues for Developers and Technologists H Khosravi1*, A Fatemi1 , P Pike2 , (1) University of Mississippi Medical Center, Jackson, MS, (2) Huntsville Hospital, Huntsville, AL |
| PO-GePV-P-8 | Importance of Vetting Test Equipment After Purchase, Repair Or Calibration: A Case Study P Brunick*, J Wang , B Helbig , J Clements , Kaiser Permanente Southern California Permanente Medical Group, Los Angeles, CA |
| PO-GePV-T-295 | Verification of Setup Accuracy with 6 Degree of Freedom Couch and CBCT T Chen*, H Wang, L Hu, J Zhang, D Barbee, J Xue, NYU Langone Medical Center, New York, NY |
| PO-GePV-U-4 | Objective Image Quality Assessment Of Trans-Rectal Ultrasound (TRUS) Systems Used In Image Guided Prostate Brachytherapy A Doyle1*, D King2 , D Cody3, F Sullivan4 , J Browne5 , (1) Technological University Dublin, Dublin, (2) Blackrock Clinic, Dublin, Ireland , (3) Technological University Dublin, Dublin, (4)Prostate Cancer Institute, National University of Ireland, Galway, (5) Mayo Clinic, Rochester, MN |
| SU-E-304-7 | The Corgi: A Multi-Purpose Modular Phantom for Dose and Image Quality Assessment in Cone-Beam CT A Uneri1*, A Hernandez2 , G Burkett2 , J Boone2 , J Siewerdsen1 , (1) Johns Hopkins University, Baltimore, MD, (2) University of California-Davis, Sacramento, CA |
| SU-I400-GePD-F6-6 | Multi-Institution Analysis of Cone-Beam CT Image Quality Performance N Becker1*, A McNiven1 , L Buckley2 , P Rapley3 , E Sabondjian4 , D Jaffray1 , D Letourneau1 , (1) The Princess Margaret Cancer Centre - University Health Network, Toronto, ON, (2) The Ottawa Hospital Regional Cancer Centre, Ottawa, ON, (3) Thunder Bay Regional Health Sciences Centre, Thunder Bay, ON, (4) Mississauga Halton/Central West Regional Cancer Program - Trillium Health Partners, Mississauga, ON |
| SU-I400-GePD-F9-1 | Accuracy of the Helically-Acquired CTDIvol as An Alternative to Traditional Methodology S Leon1*, R Kobistek2 , Z Zhang3 , E Olguin4 , I Barreto5 , B Schwarz6 , (1) University of Florida, Gainesville, FL, (2) Nat'l Physics Consultants, Ltd, Mentor, OH, (3) University of Florida, Gainesville, FL, (4) University of Florida ,Gainesville, FL, (5) University of Florida, Gainesville, FL, (6) University of Florida, Gainesville, FL |
| TH-D-302-4 | Automatic Detection of Non-Diagnostic Pediatric Lateral Airway/Soft Tissue Neck Radiographic Exams Using Deep Learning at the Point of Care E Somasundaram1*, J Dillman2 , E Crotty3 , B Coley4 , S Brady5 , (1) Cincinnati Children's Hospital Medical Center, Cincinnati, OH, (2) Cincinnati Children's Hospital, Cincinnati, OH, (3) ,Cincinnati, ,(4) Cincinnati Children's Hospital and Medical Center, Cincinnati, ,(5) Cincinnati Childrens Hospital Med Ctr, Cincinnati, OH |
| TU-F115-GePD-F8-1 | Annual Repeat/Reject Analysis for Four Mammography Units V Garcia*, W Wang , University of Oklahoma Health Science Center, Oklahoma City, OK |
| TU-J345-GePD-F8-2 | Detection and Classification of Artifacts in Structural Brain MR Images Using Deep Convolutional Neural Networks S Sujit*, R Gabr , I Coronado , P Narayana , University of Texas Health Science Center at Houston, Houston, TX |
| WE-C1030-GePD-F8-1 | Automated High Contrast Resolution Test Analysis for MRI Daily QC J Jimenez*, W Stefan , J Yung , D Reeve , R Stafford , J Hazle , UT MD Anderson Cancer Center, Houston, TX |
